As of October 2019, the Journal of Biomedical Optics (JBO) encourages authors to use structured abstracts in their manuscript submissions. JBO’s Editor-in-Chief Brian Pogue explains the transition to structured abstracts and proposes a timeline for the changeover.

Corneal collagen cross-linking (CXL) strengthens the biomechanical properties of damaged corneas. Quantifying the changes of stiffness due to different CXL protocols is difficult, especially in vivo. A noninvasive elastic wave-based optical coherence elastography system was developed to construct in vivo corneal elasticity maps by excitation of air puff. Biomechanical differences were compared for rabbit corneas given three different CXL protocols while keeping the total energy delivered constant. The Young’s modulus was weaker in corneas treated with higher irradiance levels over shorter durations, and a slight increase of Young’s modulus was present in all groups one week after the recovery process. Due to the noninvasive nature and minimal force to generate corneal elastic waves, this technique has the potential for early detection and treatment of corneal diseases in clinic.

A coaxial projective imaging (CPI) module acquires surgical scene images from the local site of surgery, transfers them wirelessly to the remote site, and projects instructive annotations to the surgical field. At the remote site, the surgical scene images are displayed, and the instructive annotations from a surgical specialist are wirelessly transferred back to the local site in order to guide the surgical intervention by a less experienced surgeon. The CPI module achieves seamless imaging of the surgical field and accurate projection of the instructive annotations, by a coaxial optical path design that couples the imaging arm with the projection arm and by a color correction algorithm that recovers the true color of the surgical scene. Our benchtop study of tele-guided intervention verifies that the proposed system has a positional accuracy of better than 1 mm at a working distance ranging from 300 to 500 mm. Our in vivo study of cricothyrotomy in a rabbit model proves the concept of tele-mentored surgical navigation. This is the first report of tele-guided surgery based on CPI. The proposed technique can be potentially used for surgical training and for telementored surgery in resource-limited settings.

Near-infrared spectroscopy (NIRS) is widely used in biomedical optics with applications ranging from basic science, such as in functional neuroimaging, to clinical, as in pulse oximetry. Despite the relatively low absorption of tissue in the near-infrared, there is still a significant amount of optical attenuation produced by the highly scattering nature of tissue. Because of this, designers of NIRS systems have to balance source optical power and source–detector separation to maximize the signal-to-noise ratio (SNR). However, theoretical estimations of SNR neglect the effects of speckle. Speckle manifests as fluctuations of the optical power received at the detector. These fluctuations are caused by interference of the multiple random paths taken by photons in tissue. We present a model for the NIRS SNR that includes the effects of speckle. We performed experimental validations with a NIRS system to show that it agrees with our model. Additionally, we performed computer simulations based on the model to estimate the contribution of speckle noise for different collection areas and source–detector separations. We show that at short source–detector separation, speckle contributes most of the noise when using long coherence length sources. Considering this additional noise is especially important for hybrid applications that use NIRS and speckle contrast simultaneously, such as in diffuse correlation spectroscopy.

The index of refraction (n) of materials and/or tissues depends on their physical properties and serves as a source of optical contrast in imaging. The variations of the index of refraction have also been investigated for diagnostic purposes in various fields, such as hematology, oncology, etc., since they can signify disease and cell dynamic changes. Optical coherence tomography (OCT) has been used in the past to measure the index ex vivo. However, most methodologies described in the literature are not appropriate for in vivo imaging since they require either a mirror below the sample or a complicated imaging setup and algorithms. We describe a technique that uses two images, obtained at different angles, to estimate the index of refraction and can, thus, also be applied in vivo. The index of refraction is calculated from the path-length difference observed by the OCT beam at the two different angles. When a reflector is not available, the path-length difference can be estimated using image registration and the cross-correlation of adjacent A-scans. The proposed technique was validated experimentally using both clear and scattering samples. The resulting values of the index of refraction were within ∼1  %   of the expected. The main limitation of this technique is the effect of misalignment on the results, requiring the precision provided by an angular-resolved OCT system. These very promising results provide evidence that the dual-angle method should be further investigated and validated on human tissues so that it can be developed into a clinically useful diagnostic tool in the future.

We developed machine learning methods to identify fibrolipidic and fibrocalcific A-lines in intravascular optical coherence tomography (IVOCT) images using a comprehensive set of handcrafted features. We incorporated features developed in previous studies (e.g., optical attenuation and A-line peaks). In addition, we included vascular lumen morphology and three-dimensional (3-D) digital edge and texture features. Classification methods were developed using expansive datasets (∼7000  images), consisting of both clinical in-vivo images and an ex-vivo dataset, which was validated using 3-D cryo-imaging/histology. Conditional random field was used to perform 3-D classification noise cleaning of classification results. We tested various multiclass approaches, classifiers, and feature selection schemes and found that a three-class support vector machine with minimal-redundancy-maximal-relevance feature selection gave the best performance. We found that inclusion of our morphological and 3-D features improved overall classification accuracy. On a held-out test set consisting of >1700 images, we obtained an overall accuracy of 81.58%, with the following (sensitivity/specificity) for each class: other (81.43/89.59), fibrolipidic (94.48/87.32), and fibrocalcific (74.82/95.28). The en-face views of classification results showed that automated classification easily captured the preponderance of a disease segment (e.g., a calcified segment had large regions of fibrocalcific classifications). Finally, we demonstrated proof-of-concept for streamlining A-line classification output with existing fibrolipidic and fibrocalcific boundary segmentation methods, to enable fully automated plaque quantification. The results suggest that our classification approach is a viable step toward fully automated IVOCT plaque classification and segmentation for live-time treatment planning and for offline assessment of drug and biologic therapeutics.

Oral cancer is a growing health issue in low- and middle-income countries due to betel quid, tobacco, and alcohol use and in younger populations of middle- and high-income communities due to the prevalence of human papillomavirus. The described point-of-care, smartphone-based intraoral probe enables autofluorescence imaging and polarized white light imaging in a compact geometry through the use of a USB-connected camera module. The small size and flexible imaging head improves on previous intraoral probe designs and allows imaging the cheek pockets, tonsils, and base of tongue, the areas of greatest risk for both causes of oral cancer. Cloud-based remote specialist and convolutional neural network clinical diagnosis allow for both remote community and home use. The device is characterized and preliminary field-testing data are shared.

Multiphoton microscopy (MPM) has the capacity to record second-harmonic generation (SHG) and endogenous two-photon excitation fluorescence (2PEF) signals emitted from biological tissues. The development of fiber-based miniaturized endomicroscopes delivering pulses in the femtosecond range will allow the transfer of MPM to clinical endoscopy. We present real-time SHG and 2PEF ex vivo images using an endomicroscope, which totally complies with clinical endoscopy regulations. This system is based on the proximal scanning of a commercial multicore image guide (IG). For understanding the inhomogeneities of the recorded images, we quantitatively characterize the IG at the single-core level during nonlinear excitation. The obtained results suggest that these inhomogeneities originate from the variable core geometries that, therefore, exhibit variable nonlinear and dispersive properties. Finally, we propose a method based on modulation of dispersion precompensation to address the image inhomogeneity issue and, as a proof of concept, we demonstrate its capability to improve the nonlinear image quality.

In the visually challenging situation of microsurgery with many altered depth cues, digitalization of surgical systems disrupts two further depth cues, namely focus and parallax. Although in purely optical surgical systems accommodation and eye movements induce expected focus and parallax changes, they become statically fixed through digitalization. Our study evaluates the impact of static focus and parallax onto performance and subjective 3D perception. Subjects reported decreased depth realism under static parallax and focus. Thus surgeons’ depth perception is impacted further through digitalization of microsurgery, increasing the potential of artificial stereo-induced fatigue.

While the nucleus-to-cytoplasmic (N:C) ratio has traditionally been used for assessing cell malignancy, most N:C measurement techniques are time-consuming and performed on thin histological sections, which prohibit assessment of three-dimensional cell structure. A combined ultrahigh frequency ultrasound (US) and photoacoustic (PA) technique was used to assess the size and N:C ratio of cultured cancer cells in three dimensions (3D). The diameters of the cells and their stained nuclei were obtained by fitting the power spectrum of backscattered US pulses and emitted PA waves, respectively, to well-established theoretical models. For comparison, an imaging flow cytometer (IFC) was also used to determine the two-dimensional cell and nucleus sizes from large cell populations using brightfield and fluorescence images, respectively. An N:C ratio was calculated for each cell using the quotient of the measured nucleus diameter and the total cell diameter. The mean N:C ratios calculated using the sound-based approach were 0.68, 0.66, and 0.54 for MCF-7, PC-3, and MDA-MB-231 cells, respectively, and were in good agreement with the corresponding values of 0.68, 0.67, and 0.68 obtained using the IFC. The combined US and PA technique, which assesses cellular N:C ratio in 3D, has potential applications in the detection of circulating tumor cells in liquid biopsies.

The silicon photomultiplier (SIPM) is an emerging detector technology that enables both high sensitivity and high dynamic range detection of visible and near-infrared light at a fraction of the cost of conventional vacuum tube photomultiplier tubes (PMTs). A low-cost detection circuit is presented and the performance of a commercial SIPM is evaluated for high-speed laser scanning microscopy applications. For moderate-to-high-speed fluorescent imaging applications, the measurements and imaging results indicate that the SIPM exceeds the sensitivity of GaAsP PMTs, while providing higher dynamic range and better saturation behavior. For low speed or applications requiring large detector areas, the GaAsP PMT retains a sensitivity advantage due to large area and lower dark counts. The calculations presented show that, above a critical detection bandwidth, the SIPM sensitivity exceeds that of a GaAsP PMT.

Confocal detection in digital scanned laser light-sheet fluorescence microscopy (DSLM) has been established as a gold standard method to improve image quality. The selective line detection of a complementary metal–oxide–semiconductor camera (CMOS) working in rolling shutter mode allows the rejection of out-of-focus and scattered light, thus reducing background signal during image formation. Most modern CMOS have two rolling shutters, but usually only a single illuminating beam is used, halving the maximum obtainable frame rate. We report on the capability to recover the full image acquisition rate via dual confocal DSLM by using an acousto-optic deflector. Such a simple solution enables us to independently generate, control and synchronize two beams with the two rolling slits on the camera. We show that the doubling of the imaging speed does not affect the confocal detection high contrast.